Function arange

dask/array/creation.py:385–467

Return evenly spaced values from `start` to `stop` with step size `step`. The values are half-open [start, stop), so including start and excluding stop. This is basically the same as python's range function but for dask arrays. When using a non-integer step, such as 0.1, the r

(start=None, /, stop=None, step=1, *, chunks="auto", like=None, dtype=None)

@array_creation_dispatch.register_inplace("numpy")
def arange(start=None, /, stop=None, step=1, *, chunks="auto", like=None, dtype=None):
    """
    Return evenly spaced values from `start` to `stop` with step size `step`.

    The values are half-open [start, stop), so including start and excluding
    stop. This is basically the same as python's range function but for dask
    arrays.

    When using a non-integer step, such as 0.1, the results will often not be
    consistent. It is better to use linspace for these cases.

    Parameters
    ----------
    start : int | float, optional
        If ``stop`` is specified, the start of interval (inclusive); otherwise, the end
        of the interval (exclusive). Default: 0 when ``stop`` is specified.
    stop : int | float
        The end of the interval (exclusive).
    step : int | float, optional
        The distance between two adjacent elements ``(out[i+1] - out[i])``.
        Must not be 0; may be negative, this results in an empty array if stop >= start.
        Default: 1.
    chunks :  int
        The number of samples on each block. Note that the last block will have
        fewer samples if ``len(array) % chunks != 0``.
        Defaults to "auto" which will automatically determine chunk sizes.
    dtype : numpy.dtype
        Output dtype. Omit to infer it from start, stop, step
        Defaults to ``None``.
    like : array type or ``None``
        Array to extract meta from. Defaults to ``None``.

    Returns
    -------
    samples : dask array

    See Also
    --------
    dask.array.linspace
    """
    if start is None and stop is None:
        raise TypeError("arange() requires stop to be specified.")
    elif start is None:
        start = 0
    elif stop is None:
        start, stop = 0, start

    # Avoid loss of precision calculating blockstart and blockstop below
    # when start is a very large int (~2**63) and step is a small float
    if start != 0 and not np.isclose(start + step - start, step, atol=0):
        r = arange(0, stop - start, step, chunks=chunks, dtype=dtype, like=like)
        return r + start

    num = int(max(np.ceil((stop - start) / step), 0))

    meta = meta_from_array(like) if like is not None else None

    if dtype is None: